Computer networks, such as the Internet, enable transmission and reception of a vast array of information. In recent years, for example, some commercial retail stores have attempted to make product information available to customers over the Internet. It is becoming increasingly popular to provide mechanisms by which consumers can indicate how favorably or unfavorably they view each product. For example, users may click a radio button or other control on a website to indicate that they “like” or “dislike” a particular product displayed on the website. The website logs the “likes” and “dislikes” received for the particular product. The number and value of “likes” and “dislikes” are indications of user endorsement of the product.
However, the “likes” and “dislikes” are logged for a particular product only on the particular website that collects this information. The “likes” and “dislikes” collected on a particular website are not available on other websites that display the same product. Additionally, “likes” and “dislikes” logged on one or multiple websites cannot be aggregated to provide an overall indication (or a factor of indication) of the users endorsement of the product. Furthermore, a particular product on a popular website may have received many “likes” and “dislikes”, but the same product on a different website may have received zero or very few “likes” and “dislikes”. The “likes” and “dislikes” for the product on the popular website cannot be attributed to the same product on the different website.
Therefore, it is desirable to make users endorsements obtained on one website available on other websites. Additionally, it is desirable to aggregate users endorsements from multiple websites into an overall indication of endorsement and to make that overall indication available on multiple websites. It is further desirable to determine an indication of endorsement for a manufacturer based on endorsements of products of the manufacturer. It is also desirable to determine endorsement trends of products and manufacturers over time and to predict product and/or product sector performance based on those trends. Furthermore, it is desirable to filter search results based on endorsements and to present advertisements based on endorsements.